A STUDY OF CONTAMINATED SOILS NEAR AN OLD COPPER SMELTER, ANACONDA, MONTANA: METAL DISTRIBUTION AND PARTITIONING WITH IMPLICATIONS FOR TRANSPORT

Nine decades of copper smelting operations in Anaconda, Montana have generated 5.7x10⁸ m³ of waste material and 16x10⁶ m² of tailings material. These operations resulted in severe degradation of the surrounding soils (777km²), contamination of groundwater and the adjacent Clark Fork River, and posed human health risks, prompting the U.S. Environmental Protection Agency to place the area on its National Priority List. Resulting from this listing, numerous studies have been conducted to identify the principal metal contaminants, which include As (1800ppm), Cd (41ppm), Cu (5200ppm), Pb (800ppm), and Zn (1900ppm).

In this study, the chemical and mineralogical characteristics of soils proximal to the tailings ponds were examined in order to identify the hydrogeochemical processes responsible for controlling the bioavailability and mobility of the contaminants. Soil cores up to 2.5m depth were collected from three sites. Sequential extractions and column leaching experiments were performed on samples taken from the cores at 30-50cm intervals. The extraction procedure followed that of Tessier et al. (Analytical Chemistry, 1979). This procedure is designed to differentiate between the adsorbed and coprecipitated metal fractions. Extractions were performed on samples dried at 60°C, then sieved to 0.25mm. The <0.25mm size fraction was selected as being the most likely fraction to have readily adsorbed the metals of interest, and to provide sufficient material for the sequential extraction analyses. Extracts were analyzed for Al, Ca, Cu, Fe, K, Mg, Mn, Zn by ICP-AES, and As, Cd, and Pb by graphite furnace AAS. In addition, the residual metal concentrations were determined following standard lithium-metaborate fusions. The column leachate experiments were conducted on columns of 25mm diameter by 250mm length, with a flow rate of 0.01L/min, in order to simulate vadose zone conditions and to develop a dynamic model of metal mobility. All results of this study were modeled using The Geochemist’s Workbench®.